minimized file size and high fidelity. By giving the ear just what it needed to hear, audio storage space was reduced by as much as 90 percent.
At first, Brandenburg worried whether his formula had any practical value. But within a few years digital music was born, and squeezing as much music as you could onto your iPod became a must. Breaking acoustic data by flexibly throwing out unmissed frequencies, Brandenburg and his colleagues had invented the MP3 compression scheme which underpins most of the music on the net. A few years after it was coined, “MP3” passed “sex” as the most searched-for term on the internet.8
We often discover that the information we need to retain is less than expected. This is what happened when Manuela Veloso and her team at Carnegie Mellon developed the CoBot, a robot helpmate that roams the hallways of a building to run errands. The team equipped the CoBot with sensors to produce a rich 3D rendering of the space in front of it. But trying to process that much data in real time was overloading the robot’s on board processors, leaving the CoBot often stuck in neutral. Dr Veloso and her team realized that the CoBot didn’t need to analyze an entire area in order to spot a wall – all it needed were three points from the same flat surface. So although the sensor records a great deal of data, its algorithm only samples a tiny fraction, using less than 10 percent of the computer’s processing power. When the algorithm identifies three points lying in the same plane, the CoBot knows it’s looking at a barrier. Just as the MP3 took advantage of the fact that the human brain doesn’t pay attention to everything it hears, the CoBot doesn’t need to “see” everything its sensors record. Its vision is barely a sketch, but it has enough of a picture to avoid bumping into obstacles. In an open field, the CoBot would be helpless, but its limited vision is perfectly adapted to a building. The intrepid machine has escorted hundreds of visitors to Dr Veloso’s office, all thanks to breaking down a whole scene to its constituent parts – like Helen’s face becoming the piece of anatomy launching the ships.
This technique of breaking down and discarding parts has created new ways to study the brain. Neuroscientists looking at brain tissue have long been stymied by the fact that the brain contains detailed circuits – but those are buried deep within the brain and are impossible to see. Scientists typically solve that problem by cutting the brain into very thin slices – one form of breaking – and then creating an image of each slice before painstakingly reassembling the entire brain in a digital simulation. However, because so many neural connections are damaged in the slicing process, the computer model is at best an approximation.
Neuroscientists Karl Deisseroth and Kwanghun Chung and their team found an alternate solution. Fatty molecules called lipids help hold the brain together, but they also diffuse light. The researchers devised a way to flush the lipids out of a dead mouse’s brain while keeping the brain’s structure intact. With the lipids gone, the mouse’s grey matter becomes transparent. Like Arcangel’s installation of the Mario Brother clouds, the CLARITY method removes part of the original but does not fill in the gaps – in this case, gaps that enable neuroscientists to study large populations of neurons in a way never before possible.9
A mouse hippocampus viewed with the CLARITY method
Breaking enables us to take something solid or continuous and fracture it into manageable pieces. Our brains parse the world into units that can then be rebuilt and reshaped.
Like bending, breaking can operate on a single source: you can pixilate an image or spin the floors of a building. But what happens when you draw on more than one source? Many creative leaps are the result of surprising combinations – whether it’s sushi pizza, houseboats, laundromat bars, or poet Marianne Moore describing a lion’s “ferocious chrysanthemum head.” For that, we turn to the brain’s third main technique for creativity.
CHAPTER 5
BLENDING
In blending, the brain combines two or more sources in novel ways. All over the world, representations of humans and animals have been blended to create mythical creatures. In ancient Greece, a man and a bull were combined to create a Minotaur. For the Egyptians, human plus lion equaled the Sphinx. In Africa, merging a woman and a fish produced a mami wata – a mermaid. What magic happened under the hood to generate these chimeras? A new merger of familiar concepts.
Brains have also blended animal with animal: the Greeks’ Pegasus was a horse with wings; the Southeast-Asian Gajasimha was half-elephant, half-lion; in English heraldry, the Allocamelus was part camel and part donkey. As with the mythology of old, our modern superheroes are often chimeric blends: Batman, Spiderman, Antman, Wolverine.
As in myth, so in science. Genetics professor Randy Lewis knew that spider silk had great commercial potential: it is many times stronger than steel.1 If only the silk could be produced in bulk, one could weave apparel such as ultra-light bulletproof vests. But it is difficult to farm spiders – when confined in large numbers, they turn into cannibals, eating each other for lunch. On top of that, harvesting silk from spiders is an arduous task: it took eighty-two people working with one million spiders several years to extract enough silk to weave forty-four square feet of cloth.2 So Lewis came up with an innovative idea: splice the DNA responsible for silk manufacturing into a goat. The result: Freckles the spider-goat. Freckles looks like a goat but she secretes spider silk in her milk. Lewis and his team milk her and then extract the strands of spider silk in the lab.3
Genetic engineering has opened up the frontier of real-life chimeras, producing not only spider-goats but also bacteria that make human insulin, fish and pigs that glow with the genes of jellyfish, and Ruppy the Puppy, the world’s first transgenic dog, who turns a fluorescent red under ultraviolet light thanks to a gene from a sea anemone.
Ruppy the Puppy in daylight and darkness
Our neural networks are adept at weaving together threads of knowledge from the natural world. Artist Joris Laarman took software that simulated the way the human skeleton develops and used it to build his “bone furniture.” Just as skeletons optimize the distribution of bone mass, Laarman’s furniture has more material where it needs to bear more weight.
In a similar vein, the Japanese engineer Eiji Nakatsu saw a blend with nature as the solution to a vexing problem. During the 1990s he was working on the bullet train to allow for faster travel times, but the existing design had an inherent drawback: the flat prow of its locomotive would create ear-shattering noise when moving at high speeds. An avid birdwatcher, Nakatsu knew that the tapered beak of the kingfisher enables it to dive into water with barely a ripple. Nakatsu’s solution for the bullet train: give the locomotive a beak. The locomotive’s bird-like nose reduces the train’s noise as it speeds along at two hundred miles an hour.
